Overview

Dataset statistics

Number of variables41
Number of observations10000
Missing cells40240
Missing cells (%)9.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.5 MiB
Average record size in memory363.0 B

Variable types

Numeric24
Text7
Categorical10

Dataset

Description경상남도 김해시 건축물 현황(건축물대장 표제부)대한 데이터로 번지주소,도로명주소,위도,경도 등의 항목을 제공합니다.
Author경상남도 김해시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15033374

Alerts

대장구분코드명 is highly imbalanced (55.2%)Imbalance
대장종류코드명 is highly imbalanced (55.2%)Imbalance
새주소도로코드 is highly imbalanced (56.2%)Imbalance
건물명 has 8571 (85.7%) missing valuesMissing
새주소법정동코드 has 906 (9.1%) missing valuesMissing
새주소본번 has 856 (8.6%) missing valuesMissing
새주소부번 has 3392 (33.9%) missing valuesMissing
대지면적(제곱미터) has 4502 (45.0%) missing valuesMissing
건축면적(제곱미터) has 428 (4.3%) missing valuesMissing
건폐율(퍼센트) has 4521 (45.2%) missing valuesMissing
용적률산정연면적(제곱미터) has 241 (2.4%) missing valuesMissing
용적률(퍼센트) has 4524 (45.2%) missing valuesMissing
높이(미터) has 3362 (33.6%) missing valuesMissing
지상층수 has 117 (1.2%) missing valuesMissing
부속건축물면적(제곱미터) has 8487 (84.9%) missing valuesMissing
총동연면적(제곱미터) has 209 (2.1%) missing valuesMissing
is highly skewed (γ1 = 26.38843362)Skewed
외필지수 is highly skewed (γ1 = 23.39060018)Skewed
대지면적(제곱미터) is highly skewed (γ1 = 42.88431154)Skewed
건축면적(제곱미터) is highly skewed (γ1 = 95.68204268)Skewed
연면적(제곱미터) is highly skewed (γ1 = 99.75358624)Skewed
총동연면적(제곱미터) is highly skewed (γ1 = 24.06993936)Skewed
순번 has unique valuesUnique
관리건축물대장 has unique valuesUnique
has 119 (1.2%) zerosZeros
has 2613 (26.1%) zerosZeros
외필지수 has 8791 (87.9%) zerosZeros
새주소부번 has 2177 (21.8%) zerosZeros
지하층수 has 9234 (92.3%) zerosZeros
승용승강기수 has 9594 (95.9%) zerosZeros
비상용승강기수 has 9809 (98.1%) zerosZeros
부속건축물수 has 8480 (84.8%) zerosZeros

Reproduction

Analysis started2023-12-10 23:23:42.925531
Analysis finished2023-12-10 23:23:45.403277
Duration2.48 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16274.212
Minimum2
Maximum32491
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:23:45.471831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile1535.95
Q18214
median16248.5
Q324425.25
95-th percentile30886.35
Maximum32491
Range32489
Interquartile range (IQR)16211.25

Descriptive statistics

Standard deviation9394.8136
Coefficient of variation (CV)0.57728223
Kurtosis-1.1989651
Mean16274.212
Median Absolute Deviation (MAD)8107
Skewness-0.01329935
Sum1.6274212 × 108
Variance88262522
MonotonicityNot monotonic
2023-12-11T08:23:45.608469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
28514 1
 
< 0.1%
11720 1
 
< 0.1%
25447 1
 
< 0.1%
2680 1
 
< 0.1%
8597 1
 
< 0.1%
2079 1
 
< 0.1%
25235 1
 
< 0.1%
21748 1
 
< 0.1%
22553 1
 
< 0.1%
7659 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
2 1
< 0.1%
11 1
< 0.1%
16 1
< 0.1%
19 1
< 0.1%
23 1
< 0.1%
27 1
< 0.1%
29 1
< 0.1%
32 1
< 0.1%
34 1
< 0.1%
38 1
< 0.1%
ValueCountFrequency (%)
32491 1
< 0.1%
32490 1
< 0.1%
32488 1
< 0.1%
32487 1
< 0.1%
32485 1
< 0.1%
32481 1
< 0.1%
32479 1
< 0.1%
32477 1
< 0.1%
32458 1
< 0.1%
32453 1
< 0.1%
Distinct8995
Distinct (%)90.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T08:23:45.939787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length43
Mean length21.587
Min length11

Characters and Unicode

Total characters215870
Distinct characters127
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8386 ?
Unique (%)83.9%

Sample

1st row경상남도 김해시 한림면 명동리 481-2번지
2nd row경상남도 김해시 지내동 103-2번지
3rd row경상남도 김해시 외동 348번지
4th row경상남도 김해시 진영읍 진영리 275-121번지
5th row경상남도 김해시 어방동 529-6번지
ValueCountFrequency (%)
경상남도 10000
22.4%
김해시 10000
22.4%
한림면 1323
 
3.0%
진영읍 1289
 
2.9%
진례면 1099
 
2.5%
주촌면 791
 
1.8%
삼방동 431
 
1.0%
진영리 423
 
0.9%
내동 349
 
0.8%
외동 343
 
0.8%
Other values (7009) 18633
41.7%
2023-12-11T08:23:46.469349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
34681
 
16.1%
10421
 
4.8%
10351
 
4.8%
10134
 
4.7%
10008
 
4.6%
10008
 
4.6%
10006
 
4.6%
10000
 
4.6%
10000
 
4.6%
9880
 
4.6%
Other values (117) 90381
41.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 133375
61.8%
Decimal Number 40385
 
18.7%
Space Separator 34681
 
16.1%
Dash Punctuation 7409
 
3.4%
Uppercase Letter 17
 
< 0.1%
Lowercase Letter 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
10421
 
7.8%
10351
 
7.8%
10134
 
7.6%
10008
 
7.5%
10008
 
7.5%
10006
 
7.5%
10000
 
7.5%
10000
 
7.5%
9880
 
7.4%
6483
 
4.9%
Other values (101) 36084
27.1%
Decimal Number
ValueCountFrequency (%)
1 8904
22.0%
2 4981
12.3%
3 4212
10.4%
4 3709
9.2%
5 3496
 
8.7%
6 3434
 
8.5%
7 3102
 
7.7%
0 3060
 
7.6%
8 2746
 
6.8%
9 2741
 
6.8%
Uppercase Letter
ValueCountFrequency (%)
L 7
41.2%
B 7
41.2%
A 3
17.6%
Space Separator
ValueCountFrequency (%)
34681
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7409
100.0%
Lowercase Letter
ValueCountFrequency (%)
i 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 133375
61.8%
Common 82475
38.2%
Latin 20
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
10421
 
7.8%
10351
 
7.8%
10134
 
7.6%
10008
 
7.5%
10008
 
7.5%
10006
 
7.5%
10000
 
7.5%
10000
 
7.5%
9880
 
7.4%
6483
 
4.9%
Other values (101) 36084
27.1%
Common
ValueCountFrequency (%)
34681
42.1%
1 8904
 
10.8%
- 7409
 
9.0%
2 4981
 
6.0%
3 4212
 
5.1%
4 3709
 
4.5%
5 3496
 
4.2%
6 3434
 
4.2%
7 3102
 
3.8%
0 3060
 
3.7%
Other values (2) 5487
 
6.7%
Latin
ValueCountFrequency (%)
L 7
35.0%
B 7
35.0%
A 3
15.0%
i 3
15.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 133375
61.8%
ASCII 82495
38.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
34681
42.0%
1 8904
 
10.8%
- 7409
 
9.0%
2 4981
 
6.0%
3 4212
 
5.1%
4 3709
 
4.5%
5 3496
 
4.2%
6 3434
 
4.2%
7 3102
 
3.8%
0 3060
 
3.7%
Other values (6) 5507
 
6.7%
Hangul
ValueCountFrequency (%)
10421
 
7.8%
10351
 
7.8%
10134
 
7.6%
10008
 
7.5%
10008
 
7.5%
10006
 
7.5%
10000
 
7.5%
10000
 
7.5%
9880
 
7.4%
6483
 
4.9%
Other values (101) 36084
27.1%


Real number (ℝ)

ZEROS 

Distinct1570
Distinct (%)15.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean606.5617
Minimum0
Maximum9350
Zeros119
Zeros (%)1.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:23:46.633770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile38
Q1245
median517
Q3919.25
95-th percentile1436
Maximum9350
Range9350
Interquartile range (IQR)674.25

Descriptive statistics

Standard deviation462.5473
Coefficient of variation (CV)0.76257255
Kurtosis22.049347
Mean606.5617
Median Absolute Deviation (MAD)313
Skewness1.9417978
Sum6065617
Variance213950.01
MonotonicityNot monotonic
2023-12-11T08:23:46.786430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 119
 
1.2%
1417 45
 
0.4%
275 30
 
0.3%
1313 29
 
0.3%
1099 29
 
0.3%
333 26
 
0.3%
309 26
 
0.3%
274 26
 
0.3%
268 26
 
0.3%
700 25
 
0.2%
Other values (1560) 9619
96.2%
ValueCountFrequency (%)
0 119
1.2%
1 4
 
< 0.1%
2 15
 
0.1%
3 4
 
< 0.1%
4 9
 
0.1%
5 8
 
0.1%
6 11
 
0.1%
7 9
 
0.1%
8 15
 
0.1%
9 12
 
0.1%
ValueCountFrequency (%)
9350 1
< 0.1%
8050 1
< 0.1%
6820 1
< 0.1%
2352 1
< 0.1%
2277 1
< 0.1%
2244 1
< 0.1%
2242 1
< 0.1%
2240 1
< 0.1%
2224 1
< 0.1%
2223 1
< 0.1%


Real number (ℝ)

SKEWED  ZEROS 

Distinct144
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.0346
Minimum0
Maximum1121
Zeros2613
Zeros (%)26.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:23:46.935385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q37
95-th percentile21
Maximum1121
Range1121
Interquartile range (IQR)7

Descriptive statistics

Standard deviation28.641638
Coefficient of variation (CV)4.0715376
Kurtosis911.24185
Mean7.0346
Median Absolute Deviation (MAD)3
Skewness26.388434
Sum70346
Variance820.34344
MonotonicityNot monotonic
2023-12-11T08:23:47.089554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2613
26.1%
1 1455
14.5%
2 925
 
9.2%
3 723
 
7.2%
4 576
 
5.8%
5 483
 
4.8%
6 389
 
3.9%
7 356
 
3.6%
8 306
 
3.1%
9 293
 
2.9%
Other values (134) 1881
18.8%
ValueCountFrequency (%)
0 2613
26.1%
1 1455
14.5%
2 925
 
9.2%
3 723
 
7.2%
4 576
 
5.8%
5 483
 
4.8%
6 389
 
3.9%
7 356
 
3.6%
8 306
 
3.1%
9 293
 
2.9%
ValueCountFrequency (%)
1121 1
< 0.1%
1112 1
< 0.1%
1105 1
< 0.1%
965 1
< 0.1%
914 1
< 0.1%
401 1
< 0.1%
382 1
< 0.1%
381 1
< 0.1%
377 1
< 0.1%
365 1
< 0.1%
Distinct8071
Distinct (%)80.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T08:23:47.441440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length27
Mean length20.633
Min length1

Characters and Unicode

Total characters206330
Distinct characters133
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7495 ?
Unique (%)75.0%

Sample

1st row 경상남도 김해시 한림면 명동로4번길 45
2nd row 경상남도 김해시 김해대로2725번길 36
3rd row 경상남도 김해시 분성로194번길 8
4th row 경상남도 김해시 진영읍 진영로 143
5th row 경상남도 김해시 인제로170번길 7
ValueCountFrequency (%)
경상남도 8936
22.5%
김해시 8936
22.5%
한림면 1200
 
3.0%
진영읍 1135
 
2.9%
진례면 988
 
2.5%
주촌면 716
 
1.8%
김해대로 278
 
0.7%
서부로 151
 
0.4%
고모로 145
 
0.4%
분성로 135
 
0.3%
Other values (4204) 17163
43.1%
2023-12-11T08:23:47.884017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
40847
19.8%
10064
 
4.9%
10006
 
4.8%
1 9877
 
4.8%
8965
 
4.3%
8945
 
4.3%
8936
 
4.3%
8936
 
4.3%
8936
 
4.3%
8699
 
4.2%
Other values (123) 82119
39.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 116270
56.4%
Decimal Number 44862
 
21.7%
Space Separator 40847
 
19.8%
Dash Punctuation 4351
 
2.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
10064
 
8.7%
10006
 
8.6%
8965
 
7.7%
8945
 
7.7%
8936
 
7.7%
8936
 
7.7%
8936
 
7.7%
8699
 
7.5%
6311
 
5.4%
6147
 
5.3%
Other values (111) 30325
26.1%
Decimal Number
ValueCountFrequency (%)
1 9877
22.0%
2 6587
14.7%
3 5060
11.3%
4 4253
9.5%
5 3701
 
8.2%
6 3501
 
7.8%
7 3258
 
7.3%
9 3119
 
7.0%
0 2765
 
6.2%
8 2741
 
6.1%
Space Separator
ValueCountFrequency (%)
40847
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4351
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 116270
56.4%
Common 90060
43.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
10064
 
8.7%
10006
 
8.6%
8965
 
7.7%
8945
 
7.7%
8936
 
7.7%
8936
 
7.7%
8936
 
7.7%
8699
 
7.5%
6311
 
5.4%
6147
 
5.3%
Other values (111) 30325
26.1%
Common
ValueCountFrequency (%)
40847
45.4%
1 9877
 
11.0%
2 6587
 
7.3%
3 5060
 
5.6%
- 4351
 
4.8%
4 4253
 
4.7%
5 3701
 
4.1%
6 3501
 
3.9%
7 3258
 
3.6%
9 3119
 
3.5%
Other values (2) 5506
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 116270
56.4%
ASCII 90060
43.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
40847
45.4%
1 9877
 
11.0%
2 6587
 
7.3%
3 5060
 
5.6%
- 4351
 
4.8%
4 4253
 
4.7%
5 3701
 
4.1%
6 3501
 
3.9%
7 3258
 
3.6%
9 3119
 
3.5%
Other values (2) 5506
 
6.1%
Hangul
ValueCountFrequency (%)
10064
 
8.7%
10006
 
8.6%
8965
 
7.7%
8945
 
7.7%
8936
 
7.7%
8936
 
7.7%
8936
 
7.7%
8699
 
7.5%
6311
 
5.4%
6147
 
5.3%
Other values (111) 30325
26.1%
Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T08:23:48.150454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length11
Mean length12.3238
Min length10

Characters and Unicode

Total characters123238
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10000 ?
Unique (%)100.0%

Sample

1st row48250-23731
2nd row48250-6272
3rd row48250-102029837
4th row48250-44984
5th row48250-22489
ValueCountFrequency (%)
48250-23731 1
 
< 0.1%
48250-34757 1
 
< 0.1%
48250-16359 1
 
< 0.1%
48250-102113944 1
 
< 0.1%
48250-34537 1
 
< 0.1%
48250-102096664 1
 
< 0.1%
48250-29547 1
 
< 0.1%
48250-39480 1
 
< 0.1%
48250-102111783 1
 
< 0.1%
48250-43988 1
 
< 0.1%
Other values (9990) 9990
99.9%
2023-12-11T08:23:48.501203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 20015
16.2%
2 19055
15.5%
4 15690
12.7%
5 15501
12.6%
8 14383
11.7%
1 10338
8.4%
- 10000
8.1%
3 5664
 
4.6%
9 4221
 
3.4%
6 4203
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 113238
91.9%
Dash Punctuation 10000
 
8.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 20015
17.7%
2 19055
16.8%
4 15690
13.9%
5 15501
13.7%
8 14383
12.7%
1 10338
9.1%
3 5664
 
5.0%
9 4221
 
3.7%
6 4203
 
3.7%
7 4168
 
3.7%
Dash Punctuation
ValueCountFrequency (%)
- 10000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 123238
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 20015
16.2%
2 19055
15.5%
4 15690
12.7%
5 15501
12.6%
8 14383
11.7%
1 10338
8.4%
- 10000
8.1%
3 5664
 
4.6%
9 4221
 
3.4%
6 4203
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 123238
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 20015
16.2%
2 19055
15.5%
4 15690
12.7%
5 15501
12.6%
8 14383
11.7%
1 10338
8.4%
- 10000
8.1%
3 5664
 
4.6%
9 4221
 
3.4%
6 4203
 
3.4%

대장구분코드명
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
일반
9065 
집합
935 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row일반
2nd row일반
3rd row일반
4th row일반
5th row일반

Common Values

ValueCountFrequency (%)
일반 9065
90.6%
집합 935
 
9.3%

Length

2023-12-11T08:23:48.620260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:23:48.714213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반 9065
90.6%
집합 935
 
9.3%

대장종류코드명
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
일반건축물
9065 
표제부
935 

Length

Max length5
Median length5
Mean length4.813
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row일반건축물
2nd row일반건축물
3rd row일반건축물
4th row일반건축물
5th row일반건축물

Common Values

ValueCountFrequency (%)
일반건축물 9065
90.6%
표제부 935
 
9.3%

Length

2023-12-11T08:23:48.813192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:23:48.904598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반건축물 9065
90.6%
표제부 935
 
9.3%

건물명
Text

MISSING 

Distinct887
Distinct (%)62.1%
Missing8571
Missing (%)85.7%
Memory size156.2 KiB
2023-12-11T08:23:49.114913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length27
Mean length8.1315605
Min length1

Characters and Unicode

Total characters11620
Distinct characters427
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique674 ?
Unique (%)47.2%

Sample

1st row장유쌍용예가
2nd row김해 롯데 워터파크
3rd row(주)태양화학
4th row율현마을 이편한세상 9단지
5th row파워텍코리아
ValueCountFrequency (%)
김해 73
 
3.4%
롯데 45
 
2.1%
워터파크 45
 
2.1%
푸르지오 32
 
1.5%
부영아파트 25
 
1.2%
진영 25
 
1.2%
아파트 22
 
1.0%
화정마을 18
 
0.8%
부영임대아파트 16
 
0.7%
단독주택 16
 
0.7%
Other values (1035) 1817
85.1%
2023-12-11T08:23:49.550226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
705
 
6.1%
353
 
3.0%
351
 
3.0%
312
 
2.7%
270
 
2.3%
245
 
2.1%
222
 
1.9%
210
 
1.8%
202
 
1.7%
199
 
1.7%
Other values (417) 8551
73.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10110
87.0%
Space Separator 705
 
6.1%
Decimal Number 388
 
3.3%
Uppercase Letter 124
 
1.1%
Close Punctuation 100
 
0.9%
Open Punctuation 100
 
0.9%
Dash Punctuation 50
 
0.4%
Lowercase Letter 26
 
0.2%
Other Punctuation 16
 
0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
353
 
3.5%
351
 
3.5%
312
 
3.1%
270
 
2.7%
245
 
2.4%
222
 
2.2%
210
 
2.1%
202
 
2.0%
199
 
2.0%
199
 
2.0%
Other values (368) 7547
74.6%
Uppercase Letter
ValueCountFrequency (%)
C 17
13.7%
I 11
 
8.9%
S 10
 
8.1%
K 10
 
8.1%
A 9
 
7.3%
B 8
 
6.5%
D 7
 
5.6%
G 6
 
4.8%
O 6
 
4.8%
Q 5
 
4.0%
Other values (11) 35
28.2%
Decimal Number
ValueCountFrequency (%)
1 97
25.0%
2 80
20.6%
3 48
12.4%
6 32
 
8.2%
5 31
 
8.0%
7 28
 
7.2%
4 25
 
6.4%
8 20
 
5.2%
9 14
 
3.6%
0 13
 
3.4%
Lowercase Letter
ValueCountFrequency (%)
e 14
53.8%
t 3
 
11.5%
o 2
 
7.7%
k 2
 
7.7%
h 2
 
7.7%
v 1
 
3.8%
i 1
 
3.8%
d 1
 
3.8%
Other Punctuation
ValueCountFrequency (%)
. 9
56.2%
, 3
 
18.8%
# 2
 
12.5%
: 1
 
6.2%
/ 1
 
6.2%
Space Separator
ValueCountFrequency (%)
705
100.0%
Close Punctuation
ValueCountFrequency (%)
) 100
100.0%
Open Punctuation
ValueCountFrequency (%)
( 100
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 50
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10107
87.0%
Common 1359
 
11.7%
Latin 151
 
1.3%
Han 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
353
 
3.5%
351
 
3.5%
312
 
3.1%
270
 
2.7%
245
 
2.4%
222
 
2.2%
210
 
2.1%
202
 
2.0%
199
 
2.0%
199
 
2.0%
Other values (367) 7544
74.6%
Latin
ValueCountFrequency (%)
C 17
 
11.3%
e 14
 
9.3%
I 11
 
7.3%
S 10
 
6.6%
K 10
 
6.6%
A 9
 
6.0%
B 8
 
5.3%
D 7
 
4.6%
G 6
 
4.0%
O 6
 
4.0%
Other values (20) 53
35.1%
Common
ValueCountFrequency (%)
705
51.9%
) 100
 
7.4%
( 100
 
7.4%
1 97
 
7.1%
2 80
 
5.9%
- 50
 
3.7%
3 48
 
3.5%
6 32
 
2.4%
5 31
 
2.3%
7 28
 
2.1%
Other values (9) 88
 
6.5%
Han
ValueCountFrequency (%)
3
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10107
87.0%
ASCII 1509
 
13.0%
CJK 3
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
705
46.7%
) 100
 
6.6%
( 100
 
6.6%
1 97
 
6.4%
2 80
 
5.3%
- 50
 
3.3%
3 48
 
3.2%
6 32
 
2.1%
5 31
 
2.1%
7 28
 
1.9%
Other values (38) 238
 
15.8%
Hangul
ValueCountFrequency (%)
353
 
3.5%
351
 
3.5%
312
 
3.1%
270
 
2.7%
245
 
2.4%
222
 
2.2%
210
 
2.1%
202
 
2.0%
199
 
2.0%
199
 
2.0%
Other values (367) 7544
74.6%
CJK
ValueCountFrequency (%)
3
100.0%
Number Forms
ValueCountFrequency (%)
1
100.0%

외필지수
Real number (ℝ)

SKEWED  ZEROS 

Distinct34
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.474
Minimum0
Maximum154
Zeros8791
Zeros (%)87.9%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:23:49.931145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum154
Range154
Interquartile range (IQR)0

Descriptive statistics

Standard deviation4.2059354
Coefficient of variation (CV)8.8732815
Kurtosis701.94571
Mean0.474
Median Absolute Deviation (MAD)0
Skewness23.3906
Sum4740
Variance17.689893
MonotonicityNot monotonic
2023-12-11T08:23:50.055827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
0 8791
87.9%
1 701
 
7.0%
2 214
 
2.1%
3 92
 
0.9%
4 68
 
0.7%
6 23
 
0.2%
5 15
 
0.1%
7 11
 
0.1%
14 9
 
0.1%
26 8
 
0.1%
Other values (24) 68
 
0.7%
ValueCountFrequency (%)
0 8791
87.9%
1 701
 
7.0%
2 214
 
2.1%
3 92
 
0.9%
4 68
 
0.7%
5 15
 
0.1%
6 23
 
0.2%
7 11
 
0.1%
8 3
 
< 0.1%
9 6
 
0.1%
ValueCountFrequency (%)
154 3
< 0.1%
108 3
< 0.1%
60 7
0.1%
52 2
 
< 0.1%
47 3
< 0.1%
41 1
 
< 0.1%
36 1
 
< 0.1%
35 1
 
< 0.1%
31 2
 
< 0.1%
30 1
 
< 0.1%

새주소도로코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
483000000000
9094 
<NA>
 
906

Length

Max length12
Median length12
Mean length11.2752
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row483000000000
2nd row483000000000
3rd row483000000000
4th row483000000000
5th row483000000000

Common Values

ValueCountFrequency (%)
483000000000 9094
90.9%
<NA> 906
 
9.1%

Length

2023-12-11T08:23:50.188107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:23:50.288149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
483000000000 9094
90.9%
na 906
 
9.1%

새주소법정동코드
Real number (ℝ)

MISSING 

Distinct126
Distinct (%)1.4%
Missing906
Missing (%)9.1%
Infinite0
Infinite (%)0.0%
Mean20222.767
Minimum10101
Maximum34013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:23:50.418545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10101
5-th percentile10301
Q111401
median12903
Q332001
95-th percentile34001
Maximum34013
Range23912
Interquartile range (IQR)20600

Descriptive statistics

Standard deviation9973.2175
Coefficient of variation (CV)0.49316781
Kurtosis-1.7151412
Mean20222.767
Median Absolute Deviation (MAD)2602
Skewness0.348287
Sum1.8390584 × 108
Variance99465067
MonotonicityNot monotonic
2023-12-11T08:23:50.587853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
25001 1091
 
10.9%
33001 929
 
9.3%
34001 886
 
8.9%
32001 684
 
6.8%
11901 353
 
3.5%
10801 325
 
3.2%
10101 276
 
2.8%
10901 226
 
2.3%
11701 223
 
2.2%
11801 216
 
2.2%
Other values (116) 3885
38.9%
(Missing) 906
 
9.1%
ValueCountFrequency (%)
10101 276
2.8%
10201 68
 
0.7%
10202 32
 
0.3%
10301 134
1.3%
10302 85
 
0.9%
10303 10
 
0.1%
10401 76
 
0.8%
10402 65
 
0.7%
10403 14
 
0.1%
10501 63
 
0.6%
ValueCountFrequency (%)
34013 114
 
1.1%
34002 201
 
2.0%
34001 886
8.9%
33004 47
 
0.5%
33002 21
 
0.2%
33001 929
9.3%
32003 40
 
0.4%
32002 18
 
0.2%
32001 684
6.8%
31001 2
 
< 0.1%

새주소본번
Real number (ℝ)

MISSING 

Distinct804
Distinct (%)8.8%
Missing856
Missing (%)8.6%
Infinite0
Infinite (%)0.0%
Mean143.51006
Minimum0
Maximum2780
Zeros53
Zeros (%)0.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:23:50.727974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4
Q115
median41
Q3120
95-th percentile635.85
Maximum2780
Range2780
Interquartile range (IQR)105

Descriptive statistics

Standard deviation320.13935
Coefficient of variation (CV)2.2307799
Kurtosis26.581235
Mean143.51006
Median Absolute Deviation (MAD)32
Skewness4.736825
Sum1312256
Variance102489.21
MonotonicityNot monotonic
2023-12-11T08:23:50.900554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3 187
 
1.9%
8 186
 
1.9%
4 180
 
1.8%
12 179
 
1.8%
7 175
 
1.8%
6 163
 
1.6%
11 163
 
1.6%
13 161
 
1.6%
9 159
 
1.6%
10 154
 
1.5%
Other values (794) 7437
74.4%
(Missing) 856
 
8.6%
ValueCountFrequency (%)
0 53
 
0.5%
1 75
0.8%
2 64
 
0.6%
3 187
1.9%
4 180
1.8%
5 147
1.5%
6 163
1.6%
7 175
1.8%
8 186
1.9%
9 159
1.6%
ValueCountFrequency (%)
2780 1
< 0.1%
2778 1
< 0.1%
2776 1
< 0.1%
2763 1
< 0.1%
2752 1
< 0.1%
2737 1
< 0.1%
2724 2
< 0.1%
2722 1
< 0.1%
2721 1
< 0.1%
2716 1
< 0.1%

새주소부번
Real number (ℝ)

MISSING  ZEROS 

Distinct147
Distinct (%)2.2%
Missing3392
Missing (%)33.9%
Infinite0
Infinite (%)0.0%
Mean13.546005
Minimum0
Maximum563
Zeros2177
Zeros (%)21.8%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:23:51.063129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median5
Q317
95-th percentile54
Maximum563
Range563
Interquartile range (IQR)17

Descriptive statistics

Standard deviation24.814981
Coefficient of variation (CV)1.831904
Kurtosis88.711375
Mean13.546005
Median Absolute Deviation (MAD)5
Skewness6.3710037
Sum89512
Variance615.78326
MonotonicityNot monotonic
2023-12-11T08:23:51.199388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2177
21.8%
1 585
 
5.9%
8 165
 
1.7%
9 165
 
1.7%
3 164
 
1.6%
5 161
 
1.6%
7 153
 
1.5%
6 149
 
1.5%
2 148
 
1.5%
12 145
 
1.5%
Other values (137) 2596
26.0%
(Missing) 3392
33.9%
ValueCountFrequency (%)
0 2177
21.8%
1 585
 
5.9%
2 148
 
1.5%
3 164
 
1.6%
4 130
 
1.3%
5 161
 
1.6%
6 149
 
1.5%
7 153
 
1.5%
8 165
 
1.7%
9 165
 
1.7%
ValueCountFrequency (%)
563 1
< 0.1%
561 1
< 0.1%
246 1
< 0.1%
245 1
< 0.1%
243 1
< 0.1%
237 2
< 0.1%
225 1
< 0.1%
224 1
< 0.1%
222 1
< 0.1%
218 1
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
0
8700 
1
1300 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 8700
87.0%
1 1300
 
13.0%

Length

2023-12-11T08:23:51.339560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:23:51.428990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 8700
87.0%
1 1300
 
13.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
주건축물
8700 
부속건축물
1300 

Length

Max length5
Median length4
Mean length4.13
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row주건축물
2nd row주건축물
3rd row주건축물
4th row주건축물
5th row주건축물

Common Values

ValueCountFrequency (%)
주건축물 8700
87.0%
부속건축물 1300
 
13.0%

Length

2023-12-11T08:23:51.532073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:23:51.622008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
주건축물 8700
87.0%
부속건축물 1300
 
13.0%

대지면적(제곱미터)
Real number (ℝ)

MISSING  SKEWED 

Distinct3272
Distinct (%)59.5%
Missing4502
Missing (%)45.0%
Infinite0
Infinite (%)0.0%
Mean3333.447
Minimum1.323
Maximum3344502
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:23:51.725500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.323
5-th percentile139.085
Q1225.75
median357.4
Q3867.75
95-th percentile3967
Maximum3344502
Range3344500.7
Interquartile range (IQR)642

Descriptive statistics

Standard deviation63559.912
Coefficient of variation (CV)19.067323
Kurtosis2057.1488
Mean3333.447
Median Absolute Deviation (MAD)164.115
Skewness42.884312
Sum18327292
Variance4.0398625 × 109
MonotonicityNot monotonic
2023-12-11T08:23:51.863209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
330.0 19
 
0.2%
228.0 17
 
0.2%
660.0 12
 
0.1%
195.0 12
 
0.1%
317.0 12
 
0.1%
264.0 11
 
0.1%
331.0 11
 
0.1%
205.0 11
 
0.1%
496.0 11
 
0.1%
231.0 11
 
0.1%
Other values (3262) 5371
53.7%
(Missing) 4502
45.0%
ValueCountFrequency (%)
1.323 1
< 0.1%
1.567 1
< 0.1%
16.631 1
< 0.1%
24.0 1
< 0.1%
35.0 1
< 0.1%
36.0 1
< 0.1%
42.0 1
< 0.1%
44.0 1
< 0.1%
45.0 2
< 0.1%
49.0 1
< 0.1%
ValueCountFrequency (%)
3344502.0 1
 
< 0.1%
2772432.0 1
 
< 0.1%
621551.5 8
0.1%
434346.0 1
 
< 0.1%
135759.0 1
 
< 0.1%
122397.27 1
 
< 0.1%
74358.6 1
 
< 0.1%
52993.0 2
 
< 0.1%
49375.6 6
0.1%
44131.1 3
 
< 0.1%

건축면적(제곱미터)
Real number (ℝ)

MISSING  SKEWED 

Distinct7114
Distinct (%)74.3%
Missing428
Missing (%)4.3%
Infinite0
Infinite (%)0.0%
Mean367.25971
Minimum0.81
Maximum594345
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:23:52.004177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.81
5-th percentile23.14
Q175.345
median132.18
Q3286.2225
95-th percentile1050.189
Maximum594345
Range594344.19
Interquartile range (IQR)210.8775

Descriptive statistics

Standard deviation6117.6445
Coefficient of variation (CV)16.657543
Kurtosis9288.034
Mean367.25971
Median Absolute Deviation (MAD)72.67
Skewness95.682043
Sum3515409.9
Variance37425574
MonotonicityNot monotonic
2023-12-11T08:23:52.125810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19.83 48
 
0.5%
6.25 36
 
0.4%
46.28 31
 
0.3%
39.67 26
 
0.3%
29.75 26
 
0.3%
33.06 25
 
0.2%
23.14 25
 
0.2%
66.0 24
 
0.2%
26.45 24
 
0.2%
60.0 24
 
0.2%
Other values (7104) 9283
92.8%
(Missing) 428
 
4.3%
ValueCountFrequency (%)
0.81 1
< 0.1%
1.0 1
< 0.1%
1.1 1
< 0.1%
1.44 1
< 0.1%
1.5 1
< 0.1%
1.56 1
< 0.1%
1.77 1
< 0.1%
1.82 2
< 0.1%
2.1 1
< 0.1%
2.3 2
< 0.1%
ValueCountFrequency (%)
594345.0 1
< 0.1%
32362.94 1
< 0.1%
23133.25 1
< 0.1%
15684.47 1
< 0.1%
14640.92 1
< 0.1%
14318.17 1
< 0.1%
14007.47 1
< 0.1%
11767.86 1
< 0.1%
9460.55 1
< 0.1%
8960.9 1
< 0.1%

건폐율(퍼센트)
Real number (ℝ)

MISSING 

Distinct3030
Distinct (%)55.3%
Missing4521
Missing (%)45.2%
Infinite0
Infinite (%)0.0%
Mean45.225068
Minimum0.0006
Maximum342.7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:23:52.252816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.0006
5-th percentile9.413
Q132.89
median51.67
Q359.33
95-th percentile67.992
Maximum342.7
Range342.6994
Interquartile range (IQR)26.44

Descriptive statistics

Standard deviation18.684139
Coefficient of variation (CV)0.41313678
Kurtosis11.119929
Mean45.225068
Median Absolute Deviation (MAD)8.23
Skewness0.10278504
Sum247788.15
Variance349.09706
MonotonicityNot monotonic
2023-12-11T08:23:52.382482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
59.5 22
 
0.2%
59.52 21
 
0.2%
59.59 20
 
0.2%
59.76 19
 
0.2%
59.58 19
 
0.2%
59.68 19
 
0.2%
59.75 19
 
0.2%
59.63 18
 
0.2%
59.71 18
 
0.2%
59.49 18
 
0.2%
Other values (3020) 5286
52.9%
(Missing) 4521
45.2%
ValueCountFrequency (%)
0.0006 1
 
< 0.1%
0.0014 3
< 0.1%
0.0024 1
 
< 0.1%
0.01 1
 
< 0.1%
0.03 1
 
< 0.1%
0.04 1
 
< 0.1%
0.0442 1
 
< 0.1%
0.07 4
< 0.1%
0.08 2
< 0.1%
0.09 2
< 0.1%
ValueCountFrequency (%)
342.7 1
 
< 0.1%
100.0 3
< 0.1%
91.79 1
 
< 0.1%
89.44 1
 
< 0.1%
88.59 1
 
< 0.1%
87.77 1
 
< 0.1%
87.76 1
 
< 0.1%
87.1 1
 
< 0.1%
86.67 1
 
< 0.1%
86.14 1
 
< 0.1%

연면적(제곱미터)
Real number (ℝ)

SKEWED 

Distinct7771
Distinct (%)78.0%
Missing32
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean1991.9258
Minimum0.81
Maximum11796871
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:23:52.508696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.81
5-th percentile21
Q182.1475
median229.18
Q3489.005
95-th percentile3494.527
Maximum11796871
Range11796870
Interquartile range (IQR)406.8575

Descriptive statistics

Standard deviation118183.97
Coefficient of variation (CV)59.331513
Kurtosis9956.4776
Mean1991.9258
Median Absolute Deviation (MAD)169.015
Skewness99.753586
Sum19855517
Variance1.3967452 × 1010
MonotonicityNot monotonic
2023-12-11T08:23:52.642279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19.83 51
 
0.5%
6.25 36
 
0.4%
46.28 31
 
0.3%
39.67 28
 
0.3%
29.75 28
 
0.3%
33.06 26
 
0.3%
23.14 25
 
0.2%
26.45 25
 
0.2%
60.0 24
 
0.2%
49.59 23
 
0.2%
Other values (7761) 9671
96.7%
(Missing) 32
 
0.3%
ValueCountFrequency (%)
0.81 2
 
< 0.1%
1.0 7
0.1%
1.1 1
 
< 0.1%
1.44 5
0.1%
1.5 1
 
< 0.1%
1.56 1
 
< 0.1%
1.77 1
 
< 0.1%
1.82 2
 
< 0.1%
1.95 1
 
< 0.1%
2.0 5
0.1%
ValueCountFrequency (%)
11796871.0 1
< 0.1%
146083.19 1
< 0.1%
67228.415 1
< 0.1%
64715.9374 1
< 0.1%
53049.5453 1
< 0.1%
46674.83 1
< 0.1%
43938.7648 1
< 0.1%
38198.1 1
< 0.1%
33308.61 1
< 0.1%
32703.79 1
< 0.1%

용적률산정연면적(제곱미터)
Real number (ℝ)

MISSING 

Distinct7632
Distinct (%)78.2%
Missing241
Missing (%)2.4%
Infinite0
Infinite (%)0.0%
Mean727.24028
Minimum0.81
Maximum92365.23
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:23:52.765955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.81
5-th percentile21.462
Q182.065
median225.6
Q3480.19
95-th percentile3142.479
Maximum92365.23
Range92364.42
Interquartile range (IQR)398.125

Descriptive statistics

Standard deviation2101.7093
Coefficient of variation (CV)2.8899793
Kurtosis401.48572
Mean727.24028
Median Absolute Deviation (MAD)166.38
Skewness12.830327
Sum7097137.9
Variance4417182.1
MonotonicityNot monotonic
2023-12-11T08:23:52.881550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19.83 51
 
0.5%
6.25 36
 
0.4%
46.28 30
 
0.3%
39.67 28
 
0.3%
29.75 27
 
0.3%
33.06 25
 
0.2%
23.14 25
 
0.2%
26.45 25
 
0.2%
49.59 22
 
0.2%
66.0 22
 
0.2%
Other values (7622) 9468
94.7%
(Missing) 241
 
2.4%
ValueCountFrequency (%)
0.81 2
 
< 0.1%
1.0 5
0.1%
1.1 1
 
< 0.1%
1.44 4
< 0.1%
1.5 1
 
< 0.1%
1.56 1
 
< 0.1%
1.77 1
 
< 0.1%
1.82 2
 
< 0.1%
1.95 1
 
< 0.1%
2.0 5
0.1%
ValueCountFrequency (%)
92365.23 1
< 0.1%
33099.99 1
< 0.1%
28894.13 1
< 0.1%
26871.522 1
< 0.1%
23150.9215 1
< 0.1%
22695.82 1
< 0.1%
22332.04 1
< 0.1%
22124.16 1
< 0.1%
22064.47 1
< 0.1%
21745.393 1
< 0.1%

용적률(퍼센트)
Real number (ℝ)

MISSING 

Distinct4650
Distinct (%)84.9%
Missing4524
Missing (%)45.2%
Infinite0
Infinite (%)0.0%
Mean96.459989
Minimum0.0006
Maximum1432.0918
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:23:52.996887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.0006
5-th percentile10.9625
Q137.2275
median68.38
Q3156.2625
95-th percentile212.5025
Maximum1432.0918
Range1432.0912
Interquartile range (IQR)119.035

Descriptive statistics

Standard deviation84.155641
Coefficient of variation (CV)0.8724409
Kurtosis21.927705
Mean96.459989
Median Absolute Deviation (MAD)44.49
Skewness2.9122607
Sum528214.9
Variance7082.1718
MonotonicityNot monotonic
2023-12-11T08:23:53.121128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
192.84 6
 
0.1%
269.37 5
 
0.1%
59.68 5
 
0.1%
39.98 5
 
0.1%
53.0 4
 
< 0.1%
59.35 4
 
< 0.1%
172.89 4
 
< 0.1%
168.58 4
 
< 0.1%
0.1 4
 
< 0.1%
39.74 4
 
< 0.1%
Other values (4640) 5431
54.3%
(Missing) 4524
45.2%
ValueCountFrequency (%)
0.0006 1
 
< 0.1%
0.0014 3
< 0.1%
0.0023 1
 
< 0.1%
0.02 1
 
< 0.1%
0.04 1
 
< 0.1%
0.0442 1
 
< 0.1%
0.05 1
 
< 0.1%
0.06 1
 
< 0.1%
0.07 1
 
< 0.1%
0.08 2
< 0.1%
ValueCountFrequency (%)
1432.0918 1
< 0.1%
897.31 1
< 0.1%
773.16 1
< 0.1%
741.15 1
< 0.1%
730.08 1
< 0.1%
709.35 1
< 0.1%
709.27 1
< 0.1%
698.97 1
< 0.1%
697.69 1
< 0.1%
697.16 1
< 0.1%

구조코드
Real number (ℝ)

Distinct18
Distinct (%)0.2%
Missing2
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean25.728546
Minimum10
Maximum99
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:23:53.233662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile11
Q121
median21
Q331
95-th percentile51
Maximum99
Range89
Interquartile range (IQR)10

Descriptive statistics

Standard deviation11.341813
Coefficient of variation (CV)0.44082604
Kurtosis1.7244982
Mean25.728546
Median Absolute Deviation (MAD)10
Skewness1.0589464
Sum257234
Variance128.63672
MonotonicityNot monotonic
2023-12-11T08:23:53.345085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
21 3474
34.7%
31 2154
21.5%
51 1008
 
10.1%
32 987
 
9.9%
12 966
 
9.7%
11 844
 
8.4%
19 427
 
4.3%
33 38
 
0.4%
41 29
 
0.3%
42 21
 
0.2%
Other values (8) 50
 
0.5%
ValueCountFrequency (%)
10 14
 
0.1%
11 844
 
8.4%
12 966
 
9.7%
19 427
 
4.3%
21 3474
34.7%
29 10
 
0.1%
31 2154
21.5%
32 987
 
9.9%
33 38
 
0.4%
34 1
 
< 0.1%
ValueCountFrequency (%)
99 9
 
0.1%
74 4
 
< 0.1%
63 2
 
< 0.1%
51 1008
10.1%
50 3
 
< 0.1%
42 21
 
0.2%
41 29
 
0.3%
39 7
 
0.1%
34 1
 
< 0.1%
33 38
 
0.4%

구조코드명
Categorical

Distinct19
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
철근콘크리트구조
3474 
일반철골구조
2154 
일반목구조
1008 
경량철골구조
987 
블록구조
966 
Other values (14)
1411 

Length

Max length13
Median length10
Mean length6.2419
Min length3

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row경량철골구조
2nd row블록구조
3rd row철근콘크리트구조
4th row블록구조
5th row철근콘크리트구조

Common Values

ValueCountFrequency (%)
철근콘크리트구조 3474
34.7%
일반철골구조 2154
21.5%
일반목구조 1008
 
10.1%
경량철골구조 987
 
9.9%
블록구조 966
 
9.7%
벽돌구조 844
 
8.4%
기타조적구조 427
 
4.3%
강파이프구조 38
 
0.4%
철골콘크리트구조 29
 
0.3%
철골철근콘크리트구조 21
 
0.2%
Other values (9) 52
 
0.5%

Length

2023-12-11T08:23:53.465132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
철근콘크리트구조 3474
34.7%
일반철골구조 2154
21.5%
일반목구조 1008
 
10.1%
경량철골구조 987
 
9.9%
블록구조 966
 
9.7%
벽돌구조 844
 
8.4%
기타조적구조 427
 
4.3%
강파이프구조 38
 
0.4%
철골콘크리트구조 29
 
0.3%
철골철근콘크리트구조 21
 
0.2%
Other values (9) 52
 
0.5%
Distinct443
Distinct (%)4.4%
Missing13
Missing (%)0.1%
Memory size156.2 KiB
2023-12-11T08:23:53.689252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length22
Mean length6.0724942
Min length2

Characters and Unicode

Total characters60646
Distinct characters90
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique265 ?
Unique (%)2.7%

Sample

1st row경량철골조
2nd row블록조
3rd row철근콘크리트구조
4th row블록조
5th row철근콘크리트조
ValueCountFrequency (%)
철근콘크리트구조 1717
16.9%
일반철골구조 1284
12.6%
철근콘크리트조 1105
10.9%
조적조 857
 
8.4%
목조 765
 
7.5%
경량철골구조 587
 
5.8%
철골조 585
 
5.7%
블럭조 389
 
3.8%
경량철골조 359
 
3.5%
블록조 295
 
2.9%
Other values (373) 2236
22.0%
2023-12-11T08:23:54.141440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
12722
21.0%
7093
11.7%
4191
 
6.9%
3927
 
6.5%
3688
 
6.1%
3615
 
6.0%
3615
 
6.0%
3606
 
5.9%
3477
 
5.7%
1584
 
2.6%
Other values (80) 13128
21.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 58846
97.0%
Other Punctuation 1535
 
2.5%
Space Separator 192
 
0.3%
Open Punctuation 31
 
0.1%
Close Punctuation 31
 
0.1%
Uppercase Letter 10
 
< 0.1%
Decimal Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
12722
21.6%
7093
12.1%
4191
 
7.1%
3927
 
6.7%
3688
 
6.3%
3615
 
6.1%
3615
 
6.1%
3606
 
6.1%
3477
 
5.9%
1584
 
2.7%
Other values (66) 11328
19.3%
Uppercase Letter
ValueCountFrequency (%)
C 3
30.0%
R 2
20.0%
A 1
 
10.0%
L 1
 
10.0%
B 1
 
10.0%
P 1
 
10.0%
E 1
 
10.0%
Other Punctuation
ValueCountFrequency (%)
/ 1314
85.6%
, 219
 
14.3%
. 2
 
0.1%
Space Separator
ValueCountFrequency (%)
192
100.0%
Open Punctuation
ValueCountFrequency (%)
( 31
100.0%
Close Punctuation
ValueCountFrequency (%)
) 31
100.0%
Decimal Number
ValueCountFrequency (%)
1 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 58846
97.0%
Common 1790
 
3.0%
Latin 10
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
12722
21.6%
7093
12.1%
4191
 
7.1%
3927
 
6.7%
3688
 
6.3%
3615
 
6.1%
3615
 
6.1%
3606
 
6.1%
3477
 
5.9%
1584
 
2.7%
Other values (66) 11328
19.3%
Common
ValueCountFrequency (%)
/ 1314
73.4%
, 219
 
12.2%
192
 
10.7%
( 31
 
1.7%
) 31
 
1.7%
. 2
 
0.1%
1 1
 
0.1%
Latin
ValueCountFrequency (%)
C 3
30.0%
R 2
20.0%
A 1
 
10.0%
L 1
 
10.0%
B 1
 
10.0%
P 1
 
10.0%
E 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 58846
97.0%
ASCII 1800
 
3.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
12722
21.6%
7093
12.1%
4191
 
7.1%
3927
 
6.7%
3688
 
6.3%
3615
 
6.1%
3615
 
6.1%
3606
 
6.1%
3477
 
5.9%
1584
 
2.7%
Other values (66) 11328
19.3%
ASCII
ValueCountFrequency (%)
/ 1314
73.0%
, 219
 
12.2%
192
 
10.7%
( 31
 
1.7%
) 31
 
1.7%
C 3
 
0.2%
R 2
 
0.1%
. 2
 
0.1%
A 1
 
0.1%
L 1
 
0.1%
Other values (4) 4
 
0.2%

주용도코드
Categorical

Distinct29
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
1000
4498 
17000
1844 
4000
1020 
2000
795 
3000
667 
Other values (24)
1176 

Length

Max length5
Median length4
Mean length4.2896
Min length4

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row17000
2nd row1000
3rd row1000
4th row3000
5th row4000

Common Values

ValueCountFrequency (%)
1000 4498
45.0%
17000 1844
18.4%
4000 1020
 
10.2%
2000 795
 
8.0%
3000 667
 
6.7%
21000 294
 
2.9%
18000 202
 
2.0%
19000 90
 
0.9%
10000 82
 
0.8%
30000 65
 
0.7%
Other values (19) 443
 
4.4%

Length

2023-12-11T08:23:54.323890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
1000 4498
45.0%
17000 1844
18.4%
4000 1020
 
10.2%
2000 795
 
8.0%
3000 667
 
6.7%
21000 294
 
2.9%
18000 202
 
2.0%
19000 90
 
0.9%
10000 82
 
0.8%
30000 65
 
0.7%
Other values (19) 443
 
4.4%
Distinct29
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
단독주택
4498 
공장
1844 
제2종근린생활시설
1020 
공동주택
795 
제1종근린생활시설
667 
Other values (24)
1176 

Length

Max length10
Median length4
Mean length4.753
Min length2

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row공장
2nd row단독주택
3rd row단독주택
4th row제1종근린생활시설
5th row제2종근린생활시설

Common Values

ValueCountFrequency (%)
단독주택 4498
45.0%
공장 1844
18.4%
제2종근린생활시설 1020
 
10.2%
공동주택 795
 
8.0%
제1종근린생활시설 667
 
6.7%
동.식물관련시설 294
 
2.9%
창고시설 202
 
2.0%
위험물저장및처리시설 90
 
0.9%
교육연구시설 82
 
0.8%
자원순환관련시설 65
 
0.7%
Other values (19) 443
 
4.4%

Length

2023-12-11T08:23:54.461639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
단독주택 4498
45.0%
공장 1844
18.4%
제2종근린생활시설 1020
 
10.2%
공동주택 795
 
8.0%
제1종근린생활시설 667
 
6.7%
동.식물관련시설 294
 
2.9%
창고시설 202
 
2.0%
위험물저장및처리시설 90
 
0.9%
교육연구시설 82
 
0.8%
자원순환관련시설 65
 
0.7%
Other values (19) 443
 
4.4%
Distinct963
Distinct (%)9.6%
Missing10
Missing (%)0.1%
Memory size156.2 KiB
2023-12-11T08:23:54.672224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length76
Median length65
Mean length6.903003
Min length2

Characters and Unicode

Total characters68961
Distinct characters256
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique665 ?
Unique (%)6.7%

Sample

1st row공해공장
2nd row단독주택
3rd row단독주택(11가구)/제2종근린생활시설
4th row근린생활시설
5th row제1,2종근린생활시설, 위락시설, 단독주택
ValueCountFrequency (%)
단독주택 2421
22.6%
공장 1521
14.2%
제2종근린생활시설 754
 
7.1%
주택 677
 
6.3%
공동주택 395
 
3.7%
제1종근린생활시설 303
 
2.8%
근린생활시설 230
 
2.2%
200
 
1.9%
단독주택/제2종근린생활시설 200
 
1.9%
근린생활시설/단독주택 193
 
1.8%
Other values (848) 3800
35.5%
2023-12-11T08:23:55.357083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5557
 
8.1%
5489
 
8.0%
4320
 
6.3%
4316
 
6.3%
3957
 
5.7%
3945
 
5.7%
3030
 
4.4%
3025
 
4.4%
2999
 
4.3%
2991
 
4.3%
Other values (246) 29332
42.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 60422
87.6%
Decimal Number 3292
 
4.8%
Other Punctuation 2657
 
3.9%
Open Punctuation 926
 
1.3%
Close Punctuation 924
 
1.3%
Space Separator 706
 
1.0%
Uppercase Letter 29
 
< 0.1%
Dash Punctuation 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
5557
 
9.2%
5489
 
9.1%
4320
 
7.1%
4316
 
7.1%
3957
 
6.5%
3945
 
6.5%
3030
 
5.0%
3025
 
5.0%
2999
 
5.0%
2991
 
5.0%
Other values (219) 20793
34.4%
Decimal Number
ValueCountFrequency (%)
2 1795
54.5%
1 1094
33.2%
4 118
 
3.6%
3 72
 
2.2%
8 55
 
1.7%
5 40
 
1.2%
0 39
 
1.2%
7 38
 
1.2%
6 26
 
0.8%
9 15
 
0.5%
Uppercase Letter
ValueCountFrequency (%)
D 8
27.6%
M 7
24.1%
F 7
24.1%
X 2
 
6.9%
G 2
 
6.9%
A 1
 
3.4%
E 1
 
3.4%
V 1
 
3.4%
Other Punctuation
ValueCountFrequency (%)
/ 1864
70.2%
, 658
 
24.8%
. 133
 
5.0%
· 1
 
< 0.1%
# 1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 926
100.0%
Close Punctuation
ValueCountFrequency (%)
) 924
100.0%
Space Separator
ValueCountFrequency (%)
706
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 60422
87.6%
Common 8510
 
12.3%
Latin 29
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
5557
 
9.2%
5489
 
9.1%
4320
 
7.1%
4316
 
7.1%
3957
 
6.5%
3945
 
6.5%
3030
 
5.0%
3025
 
5.0%
2999
 
5.0%
2991
 
5.0%
Other values (219) 20793
34.4%
Common
ValueCountFrequency (%)
/ 1864
21.9%
2 1795
21.1%
1 1094
12.9%
( 926
10.9%
) 924
10.9%
706
 
8.3%
, 658
 
7.7%
. 133
 
1.6%
4 118
 
1.4%
3 72
 
0.8%
Other values (9) 220
 
2.6%
Latin
ValueCountFrequency (%)
D 8
27.6%
M 7
24.1%
F 7
24.1%
X 2
 
6.9%
G 2
 
6.9%
A 1
 
3.4%
E 1
 
3.4%
V 1
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 60421
87.6%
ASCII 8538
 
12.4%
None 1
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
5557
 
9.2%
5489
 
9.1%
4320
 
7.1%
4316
 
7.1%
3957
 
6.5%
3945
 
6.5%
3030
 
5.0%
3025
 
5.0%
2999
 
5.0%
2991
 
5.0%
Other values (218) 20792
34.4%
ASCII
ValueCountFrequency (%)
/ 1864
21.8%
2 1795
21.0%
1 1094
12.8%
( 926
10.8%
) 924
10.8%
706
 
8.3%
, 658
 
7.7%
. 133
 
1.6%
4 118
 
1.4%
3 72
 
0.8%
Other values (16) 248
 
2.9%
None
ValueCountFrequency (%)
· 1
100.0%
Compat Jamo
ValueCountFrequency (%)
1
100.0%

지붕코드
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
10
4633 
90
3513 
30
1210 
20
623 
<NA>
 
21

Length

Max length4
Median length2
Mean length2.0042
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row90
2nd row10
3rd row10
4th row30
5th row10

Common Values

ValueCountFrequency (%)
10 4633
46.3%
90 3513
35.1%
30 1210
 
12.1%
20 623
 
6.2%
<NA> 21
 
0.2%

Length

2023-12-11T08:23:55.528147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:23:55.642219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
10 4633
46.3%
90 3513
35.1%
30 1210
 
12.1%
20 623
 
6.2%
na 21
 
0.2%

지붕코드명
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
(철근)콘크리트
4633 
기타지붕
3513 
슬레이트
1210 
기와
623 
<NA>
 
21

Length

Max length8
Median length4
Mean length5.7286
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row기타지붕
2nd row(철근)콘크리트
3rd row(철근)콘크리트
4th row슬레이트
5th row(철근)콘크리트

Common Values

ValueCountFrequency (%)
(철근)콘크리트 4633
46.3%
기타지붕 3513
35.1%
슬레이트 1210
 
12.1%
기와 623
 
6.2%
<NA> 21
 
0.2%

Length

2023-12-11T08:23:55.754028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:23:55.862826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
철근)콘크리트 4633
46.3%
기타지붕 3513
35.1%
슬레이트 1210
 
12.1%
기와 623
 
6.2%
na 21
 
0.2%
Distinct673
Distinct (%)6.8%
Missing67
Missing (%)0.7%
Memory size156.2 KiB
2023-12-11T08:23:56.161102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length21
Mean length4.8567402
Min length2

Characters and Unicode

Total characters48242
Distinct characters201
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique406 ?
Unique (%)4.1%

Sample

1st row샌드위치판넬
2nd row슬라브
3rd row경사스라브
4th row스레이트
5th row슬라브
ValueCountFrequency (%)
슬라브 2729
27.0%
스레이트 981
 
9.7%
샌드위치판넬 973
 
9.6%
철근)콘크리트 763
 
7.6%
판넬 413
 
4.1%
기타지붕 387
 
3.8%
기와 284
 
2.8%
불연판넬 226
 
2.2%
스라브 210
 
2.1%
경사슬라브 148
 
1.5%
Other values (609) 2977
29.5%
2023-12-11T08:23:56.632244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4209
 
8.7%
3856
 
8.0%
3413
 
7.1%
2904
 
6.0%
2631
 
5.5%
2535
 
5.3%
2308
 
4.8%
1522
 
3.2%
1441
 
3.0%
1333
 
2.8%
Other values (191) 22090
45.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 44927
93.1%
Open Punctuation 1025
 
2.1%
Close Punctuation 1025
 
2.1%
Other Punctuation 935
 
1.9%
Space Separator 158
 
0.3%
Decimal Number 88
 
0.2%
Uppercase Letter 69
 
0.1%
Lowercase Letter 11
 
< 0.1%
Dash Punctuation 2
 
< 0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4209
 
9.4%
3856
 
8.6%
3413
 
7.6%
2904
 
6.5%
2631
 
5.9%
2535
 
5.6%
2308
 
5.1%
1522
 
3.4%
1441
 
3.2%
1333
 
3.0%
Other values (161) 18775
41.8%
Uppercase Letter
ValueCountFrequency (%)
T 16
23.2%
K 9
13.0%
P 7
10.1%
H 6
 
8.7%
A 5
 
7.2%
S 5
 
7.2%
E 5
 
7.2%
C 4
 
5.8%
M 4
 
5.8%
N 2
 
2.9%
Other values (4) 6
 
8.7%
Decimal Number
ValueCountFrequency (%)
2 28
31.8%
0 27
30.7%
5 14
15.9%
1 13
14.8%
7 5
 
5.7%
8 1
 
1.1%
Other Punctuation
ValueCountFrequency (%)
/ 763
81.6%
, 170
 
18.2%
. 2
 
0.2%
Lowercase Letter
ValueCountFrequency (%)
m 8
72.7%
t 3
 
27.3%
Open Punctuation
ValueCountFrequency (%)
( 1025
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1025
100.0%
Space Separator
ValueCountFrequency (%)
158
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Math Symbol
ValueCountFrequency (%)
= 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 44927
93.1%
Common 3235
 
6.7%
Latin 80
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4209
 
9.4%
3856
 
8.6%
3413
 
7.6%
2904
 
6.5%
2631
 
5.9%
2535
 
5.6%
2308
 
5.1%
1522
 
3.4%
1441
 
3.2%
1333
 
3.0%
Other values (161) 18775
41.8%
Latin
ValueCountFrequency (%)
T 16
20.0%
K 9
11.2%
m 8
10.0%
P 7
8.8%
H 6
 
7.5%
A 5
 
6.2%
S 5
 
6.2%
E 5
 
6.2%
C 4
 
5.0%
M 4
 
5.0%
Other values (6) 11
13.8%
Common
ValueCountFrequency (%)
( 1025
31.7%
) 1025
31.7%
/ 763
23.6%
, 170
 
5.3%
158
 
4.9%
2 28
 
0.9%
0 27
 
0.8%
5 14
 
0.4%
1 13
 
0.4%
7 5
 
0.2%
Other values (4) 7
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 44927
93.1%
ASCII 3315
 
6.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
4209
 
9.4%
3856
 
8.6%
3413
 
7.6%
2904
 
6.5%
2631
 
5.9%
2535
 
5.6%
2308
 
5.1%
1522
 
3.4%
1441
 
3.2%
1333
 
3.0%
Other values (161) 18775
41.8%
ASCII
ValueCountFrequency (%)
( 1025
30.9%
) 1025
30.9%
/ 763
23.0%
, 170
 
5.1%
158
 
4.8%
2 28
 
0.8%
0 27
 
0.8%
T 16
 
0.5%
5 14
 
0.4%
1 13
 
0.4%
Other values (20) 76
 
2.3%

높이(미터)
Real number (ℝ)

MISSING 

Distinct1197
Distinct (%)18.0%
Missing3362
Missing (%)33.6%
Infinite0
Infinite (%)0.0%
Mean11.526142
Minimum0.95
Maximum123
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:23:56.802700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.95
5-th percentile3.65
Q16.0625
median9.5805
Q312.3
95-th percentile32.745
Maximum123
Range122.05
Interquartile range (IQR)6.2375

Descriptive statistics

Standard deviation10.728478
Coefficient of variation (CV)0.93079523
Kurtosis18.141696
Mean11.526142
Median Absolute Deviation (MAD)3.0195
Skewness3.8339223
Sum76510.529
Variance115.10024
MonotonicityNot monotonic
2023-12-11T08:23:56.994732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.5 111
 
1.1%
12.0 78
 
0.8%
4.0 77
 
0.8%
3.9 76
 
0.8%
7.9 72
 
0.7%
7.7 62
 
0.6%
11.8 62
 
0.6%
11.7 61
 
0.6%
7.3 60
 
0.6%
11.9 59
 
0.6%
Other values (1187) 5920
59.2%
(Missing) 3362
33.6%
ValueCountFrequency (%)
0.95 1
 
< 0.1%
1.8 2
 
< 0.1%
2.1 1
 
< 0.1%
2.2 3
 
< 0.1%
2.23 1
 
< 0.1%
2.4 7
0.1%
2.45 1
 
< 0.1%
2.5 7
0.1%
2.55 1
 
< 0.1%
2.6 14
0.1%
ValueCountFrequency (%)
123.0 1
 
< 0.1%
111.1 1
 
< 0.1%
109.35 1
 
< 0.1%
106.95 1
 
< 0.1%
85.4 2
< 0.1%
83.35 2
< 0.1%
82.6 3
< 0.1%
80.46 1
 
< 0.1%
79.8 1
 
< 0.1%
77.8 1
 
< 0.1%

지상층수
Real number (ℝ)

MISSING 

Distinct34
Distinct (%)0.3%
Missing117
Missing (%)1.2%
Infinite0
Infinite (%)0.0%
Mean2.3649702
Minimum1
Maximum40
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:23:57.146378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q33
95-th percentile5
Maximum40
Range39
Interquartile range (IQR)2

Descriptive statistics

Standard deviation3.292349
Coefficient of variation (CV)1.3921313
Kurtosis28.829451
Mean2.3649702
Median Absolute Deviation (MAD)0
Skewness4.9746421
Sum23373
Variance10.839562
MonotonicityNot monotonic
2023-12-11T08:23:57.305798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
1 5322
53.2%
2 1992
 
19.9%
3 1409
 
14.1%
4 545
 
5.5%
5 179
 
1.8%
15 97
 
1.0%
6 38
 
0.4%
20 36
 
0.4%
25 27
 
0.3%
7 26
 
0.3%
Other values (24) 212
 
2.1%
(Missing) 117
 
1.2%
ValueCountFrequency (%)
1 5322
53.2%
2 1992
 
19.9%
3 1409
 
14.1%
4 545
 
5.5%
5 179
 
1.8%
6 38
 
0.4%
7 26
 
0.3%
8 21
 
0.2%
9 17
 
0.2%
10 19
 
0.2%
ValueCountFrequency (%)
40 1
 
< 0.1%
39 1
 
< 0.1%
38 1
 
< 0.1%
32 1
 
< 0.1%
30 2
 
< 0.1%
29 5
 
0.1%
28 3
 
< 0.1%
27 2
 
< 0.1%
26 3
 
< 0.1%
25 27
0.3%

지하층수
Real number (ℝ)

ZEROS 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0868
Minimum0
Maximum5
Zeros9234
Zeros (%)92.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:23:57.441247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum5
Range5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.32507896
Coefficient of variation (CV)3.7451493
Kurtosis30.10004
Mean0.0868
Median Absolute Deviation (MAD)0
Skewness4.6772672
Sum868
Variance0.10567633
MonotonicityNot monotonic
2023-12-11T08:23:57.534385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 9234
92.3%
1 687
 
6.9%
2 62
 
0.6%
3 12
 
0.1%
4 4
 
< 0.1%
5 1
 
< 0.1%
ValueCountFrequency (%)
0 9234
92.3%
1 687
 
6.9%
2 62
 
0.6%
3 12
 
0.1%
4 4
 
< 0.1%
5 1
 
< 0.1%
ValueCountFrequency (%)
5 1
 
< 0.1%
4 4
 
< 0.1%
3 12
 
0.1%
2 62
 
0.6%
1 687
 
6.9%
0 9234
92.3%

승용승강기수
Real number (ℝ)

ZEROS 

Distinct13
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0759
Minimum0
Maximum25
Zeros9594
Zeros (%)95.9%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:23:57.642585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum25
Range25
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.53081764
Coefficient of variation (CV)6.9936448
Kurtosis647.46872
Mean0.0759
Median Absolute Deviation (MAD)0
Skewness19.060115
Sum759
Variance0.28176737
MonotonicityNot monotonic
2023-12-11T08:23:57.747149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 9594
95.9%
1 227
 
2.3%
2 112
 
1.1%
3 36
 
0.4%
4 13
 
0.1%
6 8
 
0.1%
5 4
 
< 0.1%
13 1
 
< 0.1%
9 1
 
< 0.1%
10 1
 
< 0.1%
Other values (3) 3
 
< 0.1%
ValueCountFrequency (%)
0 9594
95.9%
1 227
 
2.3%
2 112
 
1.1%
3 36
 
0.4%
4 13
 
0.1%
5 4
 
< 0.1%
6 8
 
0.1%
7 1
 
< 0.1%
9 1
 
< 0.1%
10 1
 
< 0.1%
ValueCountFrequency (%)
25 1
 
< 0.1%
16 1
 
< 0.1%
13 1
 
< 0.1%
10 1
 
< 0.1%
9 1
 
< 0.1%
7 1
 
< 0.1%
6 8
 
0.1%
5 4
 
< 0.1%
4 13
 
0.1%
3 36
0.4%

비상용승강기수
Real number (ℝ)

ZEROS 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0382
Minimum0
Maximum9
Zeros9809
Zeros (%)98.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:23:57.846080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum9
Range9
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.30356214
Coefficient of variation (CV)7.946653
Kurtosis197.44708
Mean0.0382
Median Absolute Deviation (MAD)0
Skewness11.199234
Sum382
Variance0.092149975
MonotonicityNot monotonic
2023-12-11T08:23:57.963313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 9809
98.1%
2 118
 
1.2%
1 43
 
0.4%
3 27
 
0.3%
9 2
 
< 0.1%
4 1
 
< 0.1%
ValueCountFrequency (%)
0 9809
98.1%
1 43
 
0.4%
2 118
 
1.2%
3 27
 
0.3%
4 1
 
< 0.1%
9 2
 
< 0.1%
ValueCountFrequency (%)
9 2
 
< 0.1%
4 1
 
< 0.1%
3 27
 
0.3%
2 118
 
1.2%
1 43
 
0.4%
0 9809
98.1%

부속건축물수
Real number (ℝ)

ZEROS 

Distinct14
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.2233
Minimum0
Maximum33
Zeros8480
Zeros (%)84.8%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:23:58.068941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum33
Range33
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.76439227
Coefficient of variation (CV)3.4231629
Kurtosis380.07563
Mean0.2233
Median Absolute Deviation (MAD)0
Skewness12.554138
Sum2233
Variance0.58429554
MonotonicityNot monotonic
2023-12-11T08:23:58.175589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
0 8480
84.8%
1 1165
 
11.7%
2 225
 
2.2%
3 57
 
0.6%
4 26
 
0.3%
6 14
 
0.1%
5 13
 
0.1%
7 10
 
0.1%
10 4
 
< 0.1%
9 2
 
< 0.1%
Other values (4) 4
 
< 0.1%
ValueCountFrequency (%)
0 8480
84.8%
1 1165
 
11.7%
2 225
 
2.2%
3 57
 
0.6%
4 26
 
0.3%
5 13
 
0.1%
6 14
 
0.1%
7 10
 
0.1%
8 1
 
< 0.1%
9 2
 
< 0.1%
ValueCountFrequency (%)
33 1
 
< 0.1%
13 1
 
< 0.1%
12 1
 
< 0.1%
10 4
 
< 0.1%
9 2
 
< 0.1%
8 1
 
< 0.1%
7 10
 
0.1%
6 14
0.1%
5 13
0.1%
4 26
0.3%

부속건축물면적(제곱미터)
Real number (ℝ)

MISSING 

Distinct1041
Distinct (%)68.8%
Missing8487
Missing (%)84.9%
Infinite0
Infinite (%)0.0%
Mean610.61685
Minimum0.6
Maximum79689.73
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:23:58.302223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.6
5-th percentile2
Q110
median42.82
Q3166.64
95-th percentile894.816
Maximum79689.73
Range79689.13
Interquartile range (IQR)156.64

Descriptive statistics

Standard deviation4303.1895
Coefficient of variation (CV)7.0472827
Kurtosis183.26526
Mean610.61685
Median Absolute Deviation (MAD)39.58
Skewness12.496585
Sum923863.29
Variance18517440
MonotonicityNot monotonic
2023-12-11T08:23:58.434393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.0 44
 
0.4%
2.88 26
 
0.3%
1.0 19
 
0.2%
3.0 15
 
0.1%
1.44 13
 
0.1%
60.0 12
 
0.1%
3.6 11
 
0.1%
12.0 11
 
0.1%
10.0 11
 
0.1%
66.0 11
 
0.1%
Other values (1031) 1340
 
13.4%
(Missing) 8487
84.9%
ValueCountFrequency (%)
0.6 1
 
< 0.1%
0.81 1
 
< 0.1%
0.99 1
 
< 0.1%
1.0 19
0.2%
1.08 1
 
< 0.1%
1.1 3
 
< 0.1%
1.2 8
0.1%
1.21 4
 
< 0.1%
1.22 1
 
< 0.1%
1.32 2
 
< 0.1%
ValueCountFrequency (%)
79689.7298 1
< 0.1%
69618.8443 2
< 0.1%
45861.98 1
< 0.1%
37372.6704 2
< 0.1%
32553.2224 1
< 0.1%
27318.0168 1
< 0.1%
25082.1681 1
< 0.1%
24427.7588 1
< 0.1%
23675.2912 1
< 0.1%
23331.2064 1
< 0.1%

총동연면적(제곱미터)
Real number (ℝ)

MISSING  SKEWED 

Distinct7561
Distinct (%)77.2%
Missing209
Missing (%)2.1%
Infinite0
Infinite (%)0.0%
Mean781.93979
Minimum0.81
Maximum145065.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:23:58.561543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.81
5-th percentile23.05
Q182.685
median230.47
Q3484.2
95-th percentile3308.7342
Maximum145065.4
Range145064.59
Interquartile range (IQR)401.515

Descriptive statistics

Standard deviation2905.9963
Coefficient of variation (CV)3.716394
Kurtosis987.76644
Mean781.93979
Median Absolute Deviation (MAD)167.53
Skewness24.069939
Sum7655972.4
Variance8444814.5
MonotonicityNot monotonic
2023-12-11T08:23:58.671821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19.83 50
 
0.5%
6.25 36
 
0.4%
46.28 29
 
0.3%
39.67 28
 
0.3%
29.75 28
 
0.3%
33.06 26
 
0.3%
23.14 25
 
0.2%
26.45 24
 
0.2%
49.59 23
 
0.2%
60.0 23
 
0.2%
Other values (7551) 9499
95.0%
(Missing) 209
 
2.1%
ValueCountFrequency (%)
0.81 1
< 0.1%
1.0 2
< 0.1%
1.1 1
< 0.1%
1.44 2
< 0.1%
1.5 1
< 0.1%
1.56 1
< 0.1%
1.77 1
< 0.1%
1.82 2
< 0.1%
2.0 2
< 0.1%
2.1 1
< 0.1%
ValueCountFrequency (%)
145065.4 1
< 0.1%
122661.03 1
< 0.1%
64715.9374 1
< 0.1%
53049.5453 1
< 0.1%
46674.83 1
< 0.1%
33308.61 1
< 0.1%
32703.79 1
< 0.1%
31298.617 1
< 0.1%
29107.6591 1
< 0.1%
28602.32 1
< 0.1%

위도
Real number (ℝ)

Distinct8838
Distinct (%)88.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.248537
Minimum35.156332
Maximum35.351494
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:23:58.788686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.156332
5-th percentile35.1793
Q135.228012
median35.239909
Q335.276661
95-th percentile35.315892
Maximum35.351494
Range0.19516272
Interquartile range (IQR)0.048649052

Descriptive statistics

Standard deviation0.039131092
Coefficient of variation (CV)0.001110148
Kurtosis-0.50248219
Mean35.248537
Median Absolute Deviation (MAD)0.021894165
Skewness0.20728081
Sum352485.37
Variance0.0015312423
MonotonicityNot monotonic
2023-12-11T08:23:58.907565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.17891261 45
 
0.4%
35.21800727 15
 
0.1%
35.2263586 15
 
0.1%
35.23677849 14
 
0.1%
35.251633 12
 
0.1%
35.19726774 12
 
0.1%
35.18959136 11
 
0.1%
35.23367134 10
 
0.1%
35.28087773 10
 
0.1%
35.31050186 9
 
0.1%
Other values (8828) 9847
98.5%
ValueCountFrequency (%)
35.15633158 8
0.1%
35.16242613 1
 
< 0.1%
35.16316868 3
 
< 0.1%
35.16370065 6
0.1%
35.16416817 1
 
< 0.1%
35.16481319 1
 
< 0.1%
35.16506123 1
 
< 0.1%
35.16510324 1
 
< 0.1%
35.16527889 1
 
< 0.1%
35.1655419 1
 
< 0.1%
ValueCountFrequency (%)
35.3514943 1
< 0.1%
35.35112271 1
< 0.1%
35.35035636 1
< 0.1%
35.3423668 1
< 0.1%
35.34221923 1
< 0.1%
35.34193963 2
< 0.1%
35.34162084 1
< 0.1%
35.34160206 1
< 0.1%
35.34144229 1
< 0.1%
35.34140112 1
< 0.1%

경도
Real number (ℝ)

Distinct8823
Distinct (%)88.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.82676
Minimum128.70585
Maximum128.93066
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T08:23:59.029794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.70585
5-th percentile128.73135
Q1128.78274
median128.82622
Q3128.87382
95-th percentile128.91061
Maximum128.93066
Range0.2248086
Interquartile range (IQR)0.0910856

Descriptive statistics

Standard deviation0.055866631
Coefficient of variation (CV)0.00043365703
Kurtosis-0.98594229
Mean128.82676
Median Absolute Deviation (MAD)0.0458624
Skewness-0.16961242
Sum1288267.6
Variance0.0031210805
MonotonicityNot monotonic
2023-12-11T08:23:59.165657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.8285602 45
 
0.4%
128.8594501 15
 
0.1%
128.8486299 15
 
0.1%
128.825249 14
 
0.1%
128.8937494 12
 
0.1%
128.8000964 12
 
0.1%
128.8433276 11
 
0.1%
128.8366542 10
 
0.1%
128.86604 10
 
0.1%
128.8937084 9
 
0.1%
Other values (8813) 9847
98.5%
ValueCountFrequency (%)
128.7058502 1
< 0.1%
128.7067793 1
< 0.1%
128.7068123 1
< 0.1%
128.7068756 1
< 0.1%
128.7076081 1
< 0.1%
128.707676 1
< 0.1%
128.7077372 1
< 0.1%
128.7077505 1
< 0.1%
128.7077564 1
< 0.1%
128.7077902 1
< 0.1%
ValueCountFrequency (%)
128.9306588 1
< 0.1%
128.9305364 1
< 0.1%
128.9295979 1
< 0.1%
128.9294211 1
< 0.1%
128.9292698 1
< 0.1%
128.9292629 1
< 0.1%
128.9289464 1
< 0.1%
128.9286097 1
< 0.1%
128.9282943 1
< 0.1%
128.9282742 1
< 0.1%

Sample

순번번지주소도로명주소관리건축물대장대장구분코드명대장종류코드명건물명외필지수새주소도로코드새주소법정동코드새주소본번새주소부번주부속구분코드주부속구분코드명대지면적(제곱미터)건축면적(제곱미터)건폐율(퍼센트)연면적(제곱미터)용적률산정연면적(제곱미터)용적률(퍼센트)구조코드구조코드명기타구조주용도코드주용도코드명기타용도지붕코드지붕코드명기타지붕높이(미터)지상층수지하층수승용승강기수비상용승강기수부속건축물수부속건축물면적(제곱미터)총동연면적(제곱미터)위도경도
2851328514경상남도 김해시 한림면 명동리 481-2번지4812경상남도 김해시 한림면 명동로4번길 4548250-23731일반일반건축물<NA>0483000000000340014500주건축물1935.01019.3952.681099.371099.3756.8132경량철골구조경량철골조17000공장공해공장90기타지붕샌드위치판넬9.020001236.971099.3735.297187128.815055
1280112802경상남도 김해시 지내동 103-2번지1032경상남도 김해시 김해대로2725번길 3648250-6272일반일반건축물<NA>0483000000000121013600주건축물575.091.0515.891.0591.0515.812블록구조블록조1000단독주택단독주택10(철근)콘크리트슬라브<NA>100014.891.0535.228864128.924808
65846585경상남도 김해시 외동 348번지3480경상남도 김해시 분성로194번길 848250-102029837일반일반건축물<NA>048300000000010901800주건축물216.0119.155.14473.82473.82219.3621철근콘크리트구조철근콘크리트구조1000단독주택단독주택(11가구)/제2종근린생활시설10(철근)콘크리트경사스라브17.050000<NA>473.8235.229205128.86795
1949519496경상남도 김해시 진영읍 진영리 275-121번지275121경상남도 김해시 진영읍 진영로 14348250-44984일반일반건축물<NA>048300000000025001143<NA>0주건축물<NA>41.32<NA>41.3241.32<NA>12블록구조블록조3000제1종근린생활시설근린생활시설30슬레이트스레이트<NA>10000<NA>41.3235.303517128.728692
1070110702경상남도 김해시 어방동 529-6번지5296경상남도 김해시 인제로170번길 748250-22489일반일반건축물<NA>048300000000011801700주건축물441.2342.6977.671922.151562.34354.1121철근콘크리트구조철근콘크리트조4000제2종근린생활시설제1,2종근린생활시설, 위락시설, 단독주택10(철근)콘크리트슬라브22.751000<NA>1922.1535.244078128.904863
1936419365경상남도 김해시 진영읍 진영리 248-5번지248548250-28879일반일반건축물<NA>2<NA><NA><NA><NA>0주건축물<NA>60.16<NA>60.1660.16<NA>51일반목구조목조3000제1종근린생활시설단독주택30슬레이트스레이트/아연<NA>10000<NA>60.1635.302682128.731125
1644616447경상남도 김해시 관동동 1077-6번지10776경상남도 김해시 관동로 6248250-102054522일반일반건축물<NA>0483000000000130026200주건축물292.5174.6459.71480.26480.26164.1921철근콘크리트구조철근콘크리트구조1000단독주택단독주택 및 제2종근린생활시설10(철근)콘크리트슬라브12.630000<NA>480.2635.177217128.810044
1527115272경상남도 김해시 신문동 530-2번지5302경상남도 김해시 장유로 36048250-102003677집합표제부장유쌍용예가294830000000001270536001부속건축물<NA><NA><NA><NA><NA><NA>21철근콘크리트구조철근콘크리트구조2000공동주택1층 필로티 주차장10(철근)콘크리트평슬라브3.9510000<NA><NA>35.194317128.815474
1064210643경상남도 김해시 어방동 505-4번지5054경상남도 김해시 활천로 16448250-11953집합표제부<NA>048300000000011803164<NA>0주건축물<NA>107.0<NA>494.4494.4<NA>21철근콘크리트구조철근콘크리트조4000제2종근린생활시설제1종근린생활시설/제2종근린생활시설10(철근)콘크리트슬라브17.450000<NA>494.435.239592128.899605
1509515096경상남도 김해시 신문동 1417번지1417048250-102104873일반일반건축물김해 롯데 워터파크0<NA><NA><NA><NA>1부속건축물<NA>6.25<NA>6.256.25<NA>51일반목구조일반목구조13000운동시설운동시설90기타지붕목구조3.910000<NA>6.2535.178913128.82856
순번번지주소도로명주소관리건축물대장대장구분코드명대장종류코드명건물명외필지수새주소도로코드새주소법정동코드새주소본번새주소부번주부속구분코드주부속구분코드명대지면적(제곱미터)건축면적(제곱미터)건폐율(퍼센트)연면적(제곱미터)용적률산정연면적(제곱미터)용적률(퍼센트)구조코드구조코드명기타구조주용도코드주용도코드명기타용도지붕코드지붕코드명기타지붕높이(미터)지상층수지하층수승용승강기수비상용승강기수부속건축물수부속건축물면적(제곱미터)총동연면적(제곱미터)위도경도
99139914경상남도 김해시 어방동 1045-6번지10456경상남도 김해시 분성로579번길 6948250-11742일반일반건축물<NA>1483000000000118016900주건축물<NA>172.8<NA>345.6345.6<NA>21철근콘크리트구조철근콘크리트조3000제1종근린생활시설제1종근린생활시설10(철근)콘크리트슬라브8.620000<NA>345.635.241521128.906834
3134631347경상남도 김해시 한림면 안하리 479-2번지479248250-43085일반일반건축물<NA>0<NA><NA><NA><NA>0주건축물<NA>26.45<NA>26.4526.45<NA>51일반목구조목조1000단독주택주택30슬레이트스레이트<NA>10000<NA>26.4535.305094128.832035
69766977경상남도 김해시 외동 산 2번지2048250-8063일반일반건축물<NA>0<NA><NA><NA><NA>0주건축물<NA>16.92<NA>16.9216.92<NA>51일반목구조목조1000단독주택단독주택30슬레이트스레이트<NA>10000<NA>16.9235.227084128.872036
3121931220경상남도 김해시 한림면 안하리 244-10번지24410경상남도 김해시 한림면 안하로116번길 5248250-102129683일반일반건축물<NA>14830000000003400152<NA>1부속건축물<NA>18.2<NA>18.218.2<NA>12블록구조블록구조17000공장공장10(철근)콘크리트(철근)콘크리트2.610000<NA>18.235.309151128.829339
1804118042경상남도 김해시 진영읍 하계리 263-1번지2631경상남도 김해시 진영읍 하계로 247-2248250-102047753일반일반건축물<NA>048300000000025001247220주건축물1018.0481.0847.26481.08481.0847.2631일반철골구조일반철골구조/블럭조4000제2종근린생활시설제2종근린생활시설90기타지붕샌드위치판넬12.510000<NA>481.0835.288091128.729345
18941895경상남도 김해시 부원동 74-27번지7427경상남도 김해시 김해대로2385번길 38-848250-47298일반일반건축물<NA>0483000000000103013880주건축물228.0135.9159.61295.8295.8129.7411벽돌구조철근콘크리트조/조적조1000단독주택단독주택10(철근)콘크리트슬라브10.330000<NA>295.835.230243128.887615
2875528756경상남도 김해시 한림면 퇴래리 1086-13번지108613경상남도 김해시 한림면 김해대로1031번안길 348250-13990일반일반건축물<NA>048300000000034001301부속건축물<NA><NA><NA>240.0<NA><NA>31일반철골구조일반철골구조17000공장공장10(철근)콘크리트슬라브<NA>20000<NA>240.035.298364128.796837
3045930460경상남도 김해시 한림면 용덕리 632-6번지6326경상남도 김해시 한림면 용덕로199번길 41-1048250-9536일반일반건축물<NA>14830000000003400141100주건축물<NA>300.0<NA>300.0300.0<NA>31일반철골구조철골조21000동.식물관련시설동물및식물관련시설90기타지붕칼라시트7.710000<NA>300.035.292139128.82701
1887518876경상남도 김해시 진영읍 진영리 1599-7번지15997경상남도 김해시 진영읍 진산대로26번길 24-2248250-102080500일반일반건축물<NA>04830000000002500124220주건축물202.1120.3259.53313.32313.32155.0321철근콘크리트구조철근콘크리트구조1000단독주택단독주택(4가구)90기타지붕슬라브11.430000<NA>313.3235.307594128.726903
70467047경상남도 김해시 흥동 283-9번지2839경상남도 김해시 칠산로 48648250-20475일반일반건축물<NA>04830000000001100148600주건축물522.0198.1737.96256.19256.1949.0831일반철골구조일반철골구조1000단독주택농가용주택/창고시설90기타지붕샌드위치판넬/슬라브8.112000165.45256.1935.21513128.85328